Abstract
Establishment of an effective R&D strategy can be achieved through Prior art search. Prior art search is aimed at identifying major applicants in a specific technology field and is mainly carried out using patents. However, some companies hide their patents as M&A or other companies with most shares in order to avoid exposure. It is difficult to identify the actual owners of patents of such patent hiding companies. Thus, patent hiding companies hinder successful prior art search. To solve this problem, this paper proposes a model for predicting patent hiding companies by using text information and quantitative indicators of patents. As experimental data, N screen technology patents registered in USPTO are used. As a result of the experiment, Cleversafe was found to be IBM's patent hiding company.
Original language | English |
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Title of host publication | ICICM 2019 - Proceedings of 2019 the 9th International Conference on Information Communication and Management |
Publisher | Association for Computing Machinery |
Pages | 123-126 |
Number of pages | 4 |
ISBN (Electronic) | 9781450371889 |
DOIs | |
Publication status | Published - 2019 Aug 23 |
Event | 9th International Conference on Information Communication and Management, ICICM 2019 - Prague, Czech Republic Duration: 2019 Aug 23 → 2019 Aug 26 |
Publication series
Name | ACM International Conference Proceeding Series |
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Conference
Conference | 9th International Conference on Information Communication and Management, ICICM 2019 |
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Country/Territory | Czech Republic |
City | Prague |
Period | 19/8/23 → 19/8/26 |
Bibliographical note
Funding Information:This research was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (NRF-2017R1D1A3B03031152). This work was supported by the National Research Foundation of Korea(NRF) grant funded by the Korea government(MSIT) (No. 2017R1A2B1010208). This work was supported by the BK21 Plus (Big Data in Manufacturing and Logistics Systems, Korea University). This research was supported by the Commercialization Promotion Agency for R&D Outcomes(COMPA) funded by the Ministry of Science and ICT(MSIT).[2019K000305]
Publisher Copyright:
© 2019 Association for Computing Machinery.
Keywords
- Latent Semantic Analysis
- Patent Hiding Company
- Patent Information Analysis
- Prior Art Search
ASJC Scopus subject areas
- Software
- Human-Computer Interaction
- Computer Vision and Pattern Recognition
- Computer Networks and Communications